This section is intended to introduce the reader to various aspects of the art that may be related to various aspects of the present invention. The following discussion is intended to provide information to facilitate a better understanding of the present invention. Accordingly, it should be understood that statements in the following discussion are to be read in this light, and not as admissions of prior art.
Policy and Charging Control (PCC) architecture permits to integrate both policy and charging control.
The architecture that supports Policy and Charging Control functionality is depicted in FIG. 1. FIG. 1 has been taken from TS 23.203, which specifies the PCC functionality for Evolved 3GPP Packet Switched domain, including both 3GPP accesses (GERAN/UTRAN/E-UTRAN) and Non-3GPP accesses.
The Gx reference point is defined in 3GPP TS 29.212 and lies between a Policy and Charging Rule Function (PCRF) and a Policy and Charging Enforcement Function (PCEF). The Gx reference point is used for provisioning and removal of PCC rules from the PCRF to the PCEF and for transmission of traffic plane events from the PCEF to the PCRF. The Gx reference point can be used for charging control, policy control or both. Note Gx reference point is generally based on Diameter (RFC 3588).
The Rx reference point is defined in 3GPP TS 29.214 and is used to exchange application level session information between the Policy and Charging Rules Function (PCRF) and an Application Function (AF). An exemplary PCRF is Ericsson Service Aware Policy Controller (SAPC). An exemplary AF is a Proxy Call Session Control Function (P-CSCF) of an IP Multimedia Subsystem (IMS). Note both Gx and Rx reference points are generally based on Diameter (RFC 3588).
DPI (Deep Packet Inspection) technology supports packet inspection and service classification, which consists on IP packets classified according to a configured tree of rules so that they are assigned to a particular service session.
DPI has been standardized in 3GPP Rel11, the so-called Traffic Detection Function (TDF), which can be either stand-alone or collocated with a PCEF, and 3GPP TR 23.813 can be consulted for details. A new reference point (Sd) has been defined between the standalone TDF and the PCRF.
When the DPI function classifies IP packets into services, enforcement actions can be done based on the service detected. One example of enforcement action is Content Enrichment (hereinafter CE), where packets are enriched with specific content, like user identification (e.g. IMSI, MSISDN) or roaming status, so that an Application Server can take decisions based on this information (e.g. deliver content tailored to the specific user). For HTTP protocol, CE consists on inserting new header fields in the HTTP header. CE also applies to other well-known protocols like SIP, SMTP, IMAP, etc.
At present, content delivery servers are used to serve contents to users. Exemplary content delivery servers may be Content Delivery Networks (CDN), Transparent Internet Caches (TIC), transcoding proxies (Transcoder), or Web servers. Specifically, when a user types a URL into his/her browser, the domain name of the URL is translated by a DNS mapping system into the IP address of a content delivery server in charge of serving the content. In order to assign the user to a server, the DNS mapping system may base its answers on historical and current data regarding global network and server conditions. This data is used to select a content delivery server that is located close to the user. Each content delivery server may be part of a CDN cloud, a large global collection of servers deployed in thousands of sites around the world. These servers are responsible for processing requests from nearby users and serving the requested content.
In this respect, a Web page may be regarded as an HTML document, which can include links to multiple objects in multiple locations. These objects are an integral part of the web page content.
Part of the content of web pages is sponsoring the main content of the web page. For example, in the case of a newspaper, the banners might be sponsoring the actual content of the web page (i.e. the news) and the infrastructure to host it.
Much of the content in current Web pages consumes a lot of bandwidth (BW). A typical download from a newspaper site requires 2 Mbytes, out of which only a few hundred Kbytes consist of textual information.
Data plans in mobile networks usually deploy a flat tariff at a given download peak rate until a certain download volume is reached. When the download limit is surpassed, the peak rate is reduced, until next billing period starts (e.g. beginning of next month).
With the introduction of faster 4G HSPA+ and LTE networks and smartphones, the download volume is increasing dramatically and this is severely affecting the data plans set for serving and charging the users.
Much of the content in current web pages includes content that consumes a lot of bandwidth. This may represent a higher use of network resources at the beginning of billing periods and cause frustration for customers when they see their peak bandwidth reduced before the accounting period ends.
There are data plans that are virtually unlimited (i.e. the download volume is not reached) under most usage conditions (e.g. when the mobile connection is not heavily used to download content). There are however others that are not (e.g. in the order of 500 KBytes downloaded before the bandwidth decrease). These are essentially targeting users needing basic connectivity such as reading e-mail and not for those intending to browse intensively.
There is no known mechanism that optimizes the user quality of experience (QoE) in accordance with the user data plan. All the mechanisms described below do not address the problem:                Web browsers currently support options to avoid downloading selected parts of the content. These options are more abundant in web browsers available for desktops than for mobile platforms.        Web servers make use of the information present in the HTTP User-Agent protocol field in order to adapt the characteristics of the downloaded content to the capabilities of the rendering device. The User-Agent is not in general a trusted source of information in order to identify the device originating an HTTP request.        Today, mobile users do adjust their behavior when they are close to hitting their bandwidth limits. Keeping an eye on mobile data plan's monthly limits (and having to deal with the consequences of going over it) is nothing new. Faster speed means there's more time to consume more content, so users must know that old habits may not fit new device's capabilities.        For instance, Netflix auto-detects how much data to send based on a user's connection, so the same movie that you watched on a 3G connection will have higher quality (and greater size) when you watch it on a 4G connection. Instead of using 100 MB to watch Netflix for an hour, you might use 200 MB.        An end-user should make adjustments to what activities are done on a mobile device. HD video streaming and video chat are among the biggest data hogs around. It's probably not a good idea to spend all day on YouTube or Netflix if you have limited data. It might be beneficial to switch to a Wi-Fi network whenever possible.        Hold off on downloading apps over the air or auto-uploading photos. iOS users should limit how many App Store visits they make on an iPhone or iPad not connected to Wi-Fi, and Android users should set auto-downloads to Wi-Fi only (Open Google Play and press Menu>Settings).        iPhone users (there are other applications for Android) have the popular DataMan to track data usage in “real-time,” so you get up-to-second monitoring of how much has been consumed. DataMan warns users about exceeding their monthly limits, and has stats that can be exported to figure out where you use data most.        Some wireless carriers also have their own apps that provide access to the subscriber's current of data usage. These apps are more accurate because they use the same accounting as the carrier, which may differ from third-party apps.        
Most of the above recommendations are habit-breakers, affecting his quality of experience, as they represent a user self-managed usage of his mobile data plan.